We extract flight routes, dynamic pricing signals, OTA comparisons, hotel rates, and car hire inventory from Skyscanner. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Flight Routes objects from skyscanner.com. All fields typed and schema-versioned.
"itinerary_id": "LHR-JFK-BA117", "origin_airport": "LHR", "destination_airport": "JFK", "airline": "British Airways", "flight_number": "BA117", "departure_time": "2026-10-12T08:25:00Z", "arrival_time": "2026-10-12T11:15:00Z", "duration_minutes": 470, "stops": 0
| # | itinerary_id | origin_airport | destination_airport | airline | flight_number | departure_time |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & OTAs objects from skyscanner.com. All fields typed and schema-versioned.
"itinerary_id": "LHR-JFK-BA117", "ota_name": "Trip.com", "price": 412.5, "currency": "GBP", "fare_class": "Economy", "baggage_included": false, "scraped_at": "2026-05-12T09:14:00Z"
| # | itinerary_id | ota_name | price | currency | deep_link | fare_class |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Hotel Inventory objects from skyscanner.com. All fields typed and schema-versioned.
"hotel_name": "The Hoxton, Williamsburg", "star_rating": 4, "price_per_night": 285.0, "total_price": 855.0, "ota_name": "Booking.com", "review_score": 8.9, "review_count": 1422
| # | hotel_id | hotel_name | location_coordinates | star_rating | price_per_night | total_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Car Hire objects from skyscanner.com. All fields typed and schema-versioned.
"pickup_location": "JFK Terminal 4", "car_type": "Compact SUV", "provider": "Hertz", "price": 64.0, "currency": "USD", "transmission": "Automatic", "mileage_policy": "Unlimited"
| # | pickup_location | dropoff_location | car_type | provider | price | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Carbon & Metadata objects from skyscanner.com. All fields typed and schema-versioned.
"flight_number": "BA117", "aircraft_type": "Boeing 777", "co2_emissions_kg": 412, "co2_difference_pct": -14, "legroom_inches": 31, "wifi_available": true, "power_outlets": true
| # | flight_number | aircraft_type | co2_emissions_kg | co2_difference_pct | legroom_inches | wifi_available |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Skyscanner scraper handles the entire aggregator lifecycle: dynamic route generation, asynchronous OTA polling, geo-targeted pricing, and anti-bot circumvention.
Origin, destination, airline, flight numbers, departure times, duration, and layover details scraped at the individual leg level.
Capture live pricing across dozens of OTAs and direct airline feeds for a single itinerary, timestamped per crawl.
Extract prices based on specific point-of-sale IP locations to monitor regional price discrimination and currency variations.
Extract hotel names, star ratings, aggregate review scores, and nightly rates across multiple booking platforms.
Provider names, vehicle classes, transmission types, and rental policies mapped against daily rates.
Extract Greener Choice labels, CO2 emission calculations in kilograms, and percentage differences from route averages.
Identify basic economy restrictions, included cabin baggage, checked luggage fees, and ticket flexibility.
Support for complex itinerary configurations including open-jaw tickets and multi-stop global routing.
Run one-off bulk exports or configure continuous pipelines at hourly, daily, or real-time cadences with change-detection diffing.
Brief in. Clean data out.
Provide airport pairs, date ranges, or hotel locations. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for skyscanner.com.
Schema validation, null-rate checks, price-outlier detection, and sample routes before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Aggregators invest heavily in scraping detection. Here is how we stay resilient - and why teams choose managed infrastructure over DIY.
Skyscanner employs aggressive bot detection. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management to maintain access.
Flight results load progressively as Skyscanner queries backend OTAs. Our Playwright scripts monitor network idle states and DOM mutations to ensure all third-party prices populate before extraction.
Flight prices change based on the user location. We route requests through specific country-level proxy nodes to extract accurate local pricing and currency data.
Aggregator DOM structures mutate constantly. Our selector strategy uses multiple fallback chains per field - CSS selectors, XPath, and text-pattern matching - ensuring continuous data flow.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, price outliers, schema drift, and coverage drops.
Airlines and OTAs monitor competitor pricing, fare class availability, and direct-booking parity across routes.
Pricing teams analyse market demand signals, competitor load factors, and pricing curves to optimise their own seat inventory.
Enterprise travel managers audit internal booking tools against public aggregator rates to ensure policy compliance.
Analysts track route capacity, new airline entries, and regional pricing trends to identify underserved markets.
Niche travel startups use aggregator data to build specialised booking experiences or dynamic package holidays.
Machine learning models train on historical pricing and duration data to predict future fare drops and optimal booking windows.
"Skyscanner aggregates the global travel market, but extracting that pricing matrix requires navigating severe anti-bot protections and asynchronous data loads."
Most teams underestimate the compute required to scrape flight aggregators. Reliable Skyscanner extraction requires geo-targeted residential proxies, full JavaScript execution, and dynamic wait times for OTA polling. DataFlirt absorbs that complexity so your engineers can focus on pricing models.
Everything supported by our skyscanner.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration and retry logic. Playwright manages JavaScript rendering, cookie sessions, and OTA polling waits.
We maintain pools of residential ISP proxies across global regions. Rotation happens per-request to ensure accurate point-of-sale pricing.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About skyscanner.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available pricing and route information is generally permissible under applicable law. DataFlirt targets only public, non-authenticated travel data. We do not extract personal data or circumvent authentication walls. Clients should review terms of service and consult legal counsel for specific use cases.
Skyscanner loads OTA prices asynchronously. Our Playwright implementation monitors network traffic and DOM mutations, waiting until the loading indicator resolves before extracting the final price matrix.
Yes. We route requests through country-specific residential proxies to mimic local users, ensuring you capture accurate geo-targeted pricing and currency variations.
Real-time streaming pipelines achieve sub-5-minute latency for specific route queries. Bulk catalogue refreshes complete within agreed SLA windows depending on route volume.
Yes. Our schema supports complex itinerary arrays, capturing each leg of a multi-city journey or return flight independently while maintaining the total trip price.
Absolutely. We provide a sample run of up to 100 route pairs as part of the pre-engagement scoping process, allowing you to validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off route export or continuous price-monitoring across 10,000 airport pairs - we scope, build, and operate the pipeline. Tell us what you need.
